The candidate's PhD work focused on the Lokomat robotic gait training device and measuring the actual forces that patients exerted during training in this device. As a postdoc he is currently investigating the ability of a rodent robotic gait training device to restore over ground locomotion following cervical spinal cord injury and the underlying plasticity of the central nervous system in response to the training. In both human and animal robotic gait trainers, the training consists of actively guiding the limbs through a symmetric healthy gait pattern. As an independent researcher the candidate proposes to study different training patterns, specifically training within asymmetric force fields, in order to findthe optimal robotic training. Asymmetric training can also be applied to other tasks, such as skilled reaching. Therefore, the candidate intends to show that the asymmetric training of both locomotion and reaching will lead to greater functional improvements in a variety of tasks and greater neuronal plasticity than the conventional symmetric training. By uncovering the optimal training techniques in animal models, clinical training practices may then be improved.